Why Do You Find the Review Useful? The Trilogy of Intensity, Discrepancy, and Credibility

Project: Research

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Online review systems have become the de facto mechanism for communicating product quality and seller trustworthiness in online marketplaces. An online review typically consists of a numerical rating and a text comment. In the common case where a product consists of many online reviews, it is impossible for the users to go through all the reviews and identify the useful ones. The ability of online review systems to effectively identify the useful reviews and present them to the users becomes important. Drawing on Information Adoption Model (Sussman and Siegal 2003) and Information Processing Theory of Language Intensity (Hamilton et al. 1990; Hamilton and Stewart 1993; Hamilton 1997; Hamilton and Hunter 1998), we examine three antecedents of review usefulness - language intensity (specificity and emotionality), message discrepancy, and source credibility. The research model will be examined through an empirical study using online review data from Amazon and a controlled experiment. In addition, quantitative measures in computational linguistics will be explored for the operationalization of language intensity and examined on their effectiveness in identifying useful online reviews. The findings will provide insights on the theoretical determinants of review usefulness, and how they can be practically implemented by online review systems to identify and present useful online reviews on a large scale.


Project number9041598
Grant typeGRF
Effective start/end date1/01/1127/03/13